Mitochondria are complex organelles at the center of cellular metabolism, apoptosis, and signaling. They continue to be the subject of intense basic investigation to understand their composition and function, but they have also captivated the attention of clinical researchers because of the growing knowledge of the (sometimes unexpected) roles of mitochondria in human diseases and aging. A full understanding of these intriguing organelles often requires their purification from cells or tissues under specific physiological or pathological conditions. Here we provide some introductory considerations for those interested in purifying mitochondria for subsequent downstream biophysical, structural, and functional analysis.

The number of mitochondria per cell varies substantially from cell line to cell line. For example, human HeLa cells contain at least twice as many mitochondria as smaller mouse L cells. This protocol starts with a washed cell pellet of 1-2 mL derived from ∼10⁹ cells grown in culture. The cells are swollen in a hypotonic buffer and ruptured with a Dounce or Potter-Elvehjem homogenizer using a tight-fitting pestle, and mitochondria are isolated by differential centrifugation.

Ionotropic glutamate receptors (iGluRs) at postsynaptic terminals mediate the majority of fast excitatory neurotransmission in response to release of glutamate from the presynaptic terminal. Obtaining structural information on the molecular organization of iGluRs in their native environment, along with other signaling and scaffolding proteins in the postsynaptic density (PSD), and associated proteins on the presynaptic terminal, would enhance understanding of the molecular basis for excitatory synaptic transmission in normal and in disease states. Cryo-electron tomography (ET) studies of synaptosomes is one attractive vehicle by which to study iGluR-containing excitatory synapses. Here we describe a workflow for the preparation of glutamatergic synaptosomes for cryo-ET studies. We describe the utilization of fluorescent markers for the facile detection of the pre and postsynaptic terminals of glutamatergic synaptosomes using cryo-laser scanning confocal microscope (cryo-LSM). We further provide the details for preparation of lamellae, between ~100 to 200 nm thick, of glutamatergic synaptosomes using cryo-focused ion-beam (FIB) milling. We monitor the lamella preparation using a scanning electron microscope (SEM) and following lamella production, we identify regions for subsequent cryo-ET studies by confocal fluorescent imaging, exploiting the pre and postsynaptic fluorophores.

Targeting small-molecule fluorescent indicators using genetically encoded protein tags yields new hybrid sensors for biological imaging. Optimization of such systems requires redesign of the synthetic indicator to allow cell-specific targeting without compromising the photophysical properties or cellular performance of the small-molecule probe. We developed a bright and sensitive Ca indicator by systematically exploring the relative configuration of dye and chelator, which can be targeted using the HaloTag self-labeling tag system. Our "isomeric tuning" approach is generalizable, yielding a far-red targetable indicator to visualize Ca fluxes in the primary cilium.

Transfer of autoantibodies targeting ionotropic N-methyl-D-aspartate receptors in autoimmune encephalitis patients into mice leads to typical disease signs. Long-term effects of the pathogenic antibodies consist of immunoglobulin G-induced crosslinking and receptor internalization. We focused on the direct and immediate impact of a specific pathogenic patient-derived monoclonal autoantibody (immunoglobulin G #003-102) on receptor function.We performed cell-attached recordings in cells transfected with the GluN1 and GluN2A subunit of the N-methyl-D-aspartate receptor. Immunoglobulin G #003-102 binds to the amino-terminal domain of the glycine-binding GluN1 subunit. It reduced simultaneous receptor openings significantly compared to controls at both low and high glutamate and glycine concentrations. Closer examination of our data in 50-second to 2-second intervals revealed, that Immunoglobulin G #003-102 rapidly decreases the number of open receptors. However, antigen-binding fragments of immunoglobulin G #003-102 did not reduce the receptor openings.In conclusion, patient-derived immunoglobulin G #003-102 inhibits N-methyl-D-aspartate receptors rapidly and directly before receptor internalization occurs and the entire immunoglobulin G is necessary for this acute inhibitory effect. This suggests an application of the antigen-binding fragment-like constructs of #003-102 as a potential new treatment strategy for shielding the pathogenic epitopes on the N-methyl-D-aspartate receptors.

An automated ultra-microtome capable of sectioning thousands of ultrathin sections onto standard TEM slot grids was developed and used to section: a complete Drosophila melanogaster first-instar larva, three sections per grid, into 4,866 34-nm-thick sections with a cutting and pickup success rate of 99.74%; 30 microns of mouse cortex measuring roughly 400 um x 2000 um at 40 nm per slice; and a full adult Drosophila brain and ventral nerve column into 9,300 sections with a pickup success rate of 99.95%. The apparatus uses optical interferometers to monitor a reference distance between the cutting knife and multiple sample blocks. Cut sections are picked up from the knife-boat water surface while they are still anchored to the cutting knife. Blocks without embedded tissue are used to displace tissue-containing sections away from the knife edge so that the tissue regions end up in the grid slot instead of on the grid rim.

We present a machine learning–based system for automatically computing interpretable, quantitative measures of animal behavior. Through our interactive system, users encode their intuition about behavior by annotating a small set of video frames. These manual labels are converted into classifiers that can automatically annotate behaviors in screen-scale data sets. Our general-purpose system can create a variety of accurate individual and social behavior classifiers for different organisms, including mice and adult and larval Drosophila.

Janelia Farm, the new research campus of the Howard Hughes Medical Institute, is an ongoing experiment in the social engineering of research communities.

Sexual behaviors in animals are governed by inputs from multiple external sensory modalities. However, how these inputs are integrated to jointly control animal behavior is still poorly understood. Whereas visual information alone is not sufficient to induce courtship behavior in Drosophila melanogaster males, when a subset of male-specific fruitless (fru)- and doublesex (dsx)-expressing neurons that respond to chemosensory cues (P1 neurons) were artificially activated via a temperature-sensitive cation channel (dTRPA1), males followed and extended their wing toward moving objects (even a moving piece of rubber band) intensively. When stationary, these objects were not courted. Our results indicate that motion input and activation of P1 neurons are individually necessary, and under our assay conditions, jointly sufficient to elicit early courtship behaviors, and provide insights into how courtship decisions are made via sensory integration.

Large electron microscopy image datasets for connectomics are typically composed of thousands to millions of partially overlapping two-dimensional images (tiles), which must be registered into a coherent volume prior to further analysis. A common registration strategy is to find matching features between neighboring and overlapping image pairs, followed by a numerical estimation of optimal image deformation using a so-called solver program. 
Existing solvers are inadequate for large data volumes, and inefficient for small-scale image registration. 
In this work, an efficient and accurate matrix-based solver method is presented. A linear system is constructed that combines minimization of feature-pair square distances with explicit constraints in a regularization term. In absence of reliable priors for regularization, we show how to construct a rigid-model approximation to use as prior. The linear system is solved using available computer programs, whose performance on typical registration tasks we briefly compare, and to which future scale-up is delegated. Our method is applied to the joint alignment of 2.67 million images, with more than 200 million point-pairs and has been used for successfully aligning the first full adult fruit fly brain.